Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli

Insights on the Advancements of In Silico Metabolic Studies of Succinic Acid Producing Microorganisms: A Review with Emphasis on Actinobacillus succinogenes

Succinic acid (SA) is one of the top candidate value-added chemicals that can be produced from biomass via microbial fermentation. A considerable number of cell factories have been proposed in the past two decades as native as well as non-native SA producers. Actinobacillus succinogenes is among the best and earliest known natural SA producers. However, its industrial application has not yet been realized due to various underlying challenges. Previous studies revealed that the optimization of environmental conditions alone could not entirely resolve these critical problems. On the other hand, microbial in silico metabolic modeling approaches have lately been the center of attention and have been applied for the efficient production of valuable commodities including SA. Then again, literature survey results indicated the absence of up-to-date reviews assessing this issue, specifically concerning SA production. Hence, this review was designed to discuss accomplishments and future perspectives of in silico studies on the metabolic capabilities of SA producers. Herein, research progress on SA and A. succinogenes, pathways involved in SA production, metabolic models of SA-producing microorganisms, and status, limitations and prospects on in silico studies of A. succinogenes were elaborated. All in all, this review is believed to provide insights to understand the current scenario and to develop efficient mathematical models for designing robust SA-producing microbial strains.

Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli

The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite’s production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment.

In silico evolution of Aspergillus niger organic acid production suggests strategies for switching acid output

BACKGROUND

The fungus Aspergillus niger is an important industrial organism for citric acid fermentation; one of the most efficient biotechnological processes. Previously we introduced a dynamic model that captures this process in the industrially relevant batch fermentation setting, providing a more accurate predictive platform to guide targeted engineering. In this article we exploit this dynamic modelling framework, coupled with a robust genetic algorithm for the in silico evolution of A. niger organic acid production, to provide solutions to complex evolutionary goals involving a multiplicity of targets and beyond the reach of simple Boolean gene deletions. We base this work on the latest metabolic models of the parent citric acid producing strain ATCC1015 dedicated to organic acid production with the required exhaustive genomic coverage needed to perform exploratory in silico evolution.

RESULTS

With the use of our informed evolutionary framework, we demonstrate targeted changes that induce a complete switch of acid output from citric to numerous different commercially valuable target organic acids including succinic acid. We highlight the key changes in flux patterns that occur in each case, suggesting potentially valuable targets for engineering. We also show that optimum acid productivity is achieved through a balance of organic acid and biomass production, requiring finely tuned flux constraints that give a growth rate optimal for productivity.

CONCLUSIONS

This study shows how a genome-scale metabolic model can be integrated with dynamic modelling and metaheuristic algorithms to provide solutions to complex metabolic engineering goals of industrial importance. This framework for in silico guided engineering, based on the dynamic batch growth relevant to industrial processes, offers considerable potential for future endeavours focused on the engineering of organisms to produce valuable products.

Effect of dissolved oxygen on L-methionine production from glycerol by Escherichia coli W3110BL using metabolic flux analysis method

L-Methionine is an essential amino acid in humans, which plays an important role in the synthesis of some important amino acids and proteins. In this work, metabolic flux of batch fermentation of L-methionine with recombinant Escherichia coli W3110BL was analyzed using the flux balance analysis method, which estimated the intracellular flux distributions under different dissolved oxygen conditions. The results revealed the producing L-methionine flux of 4.8 mmol/(g cell·h) [based on the glycerol uptake flux of 100 mmol/(g cell·h)] was obtained at 30% dissolved oxygen level which was higher than that of other dissolved oxygen levels. The carbon fluxes for synthesizing L-methionine were mainly obtained from the pathway of phosphoenolpyruvate to oxaloacetic acid [15.6 mmol/(g cell·h)] but not from the TCA cycle. Hence, increasing the flow from phosphoenolpyruvate to oxaloacetic acid by enhancing the enzyme activity of phosphoenolpyruvate carboxylase might be conducive to the production of L-methionine. Additionally, pentose phosphate pathway could provide a large amount of reducing power NADPH for the synthesis of amino acids and the flux could increase from 41 mmol/(g cell·h) to 51 mmol/(g cell·h) when changing the dissolved oxygen levels, thus meeting the requirement of NADPH for L-methionine production and biomass synthesis. Therefore, the following modification of the strains should based on the improvement of the key pathway and the NAD(P)/NAD(P)H metabolism.